Effects of a 24‐hr‐shift‐related short‐term sleep deprivation on cardiac function: A cardiac magnetic resonance‐based study

Kuetting, Daniel; Feißt, Andreas; Sprinkart, Alois M.; Homsi, Rami; Luetkens, Julian A.; Thomas, Daniel; Schild, Hans H.; Dabir, Darius

doi:10.1111/jsr.12665

Cited by 25 publications

(23 citation statements)

References 34 publications

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“…This may support physician ability to adapt to the workload and stressful events during a 24-h on-call-shift, and TSH alterations may function as a first indicator of such an effect as other biochemical stress parameters, e.g., cortisol, epinephrine, norepinephrine, insulin and glucagon, did not show significant changes. An increasing trend in hormonal values was determined also in the study by Kuetting et al [24] that observed significantly higher levels of TSH, FT3 and FT4 in German radiology residents following 24-h shift and work-related short-term partial sleep deprivation, compared to the values detected before the shift, while no significant changes were observed before and after a regular day of work and regular sleep.…”

Section: Night On-call-work and Thyroid Hormonal Changessupporting

confidence: 53%

“…Overall, our search retrieved a total of 13 articles suitable for review ( Figure 1). Most of the reviewed studies assessed the association between shift-work and night-work and thyroid hormonal changes in different occupational settings [20][21][22][23][24][25][26][27][28][29] ( Table 1). Only a few publications focused on possible clinical adverse outcomes [26,[30][31][32].…”

Section: Resultsmentioning

confidence: 99%

“…When the effects of a night or 24-h on-call duty were investigated on the TSH levels, conflicting results were reported [22,24,25]. A significant increase in TSH levels was demonstrated by Harbeck et al [22] in German internal medicine physicians the morning after a 24-h on-call-duty, compared to the TSH levels determined before a normal working day.…”

Section: Night On-call-work and Thyroid Hormonal Changesmentioning

confidence: 99%

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The Impact of Shift-Work and Night Shift-Work on Thyroid: A Systematic Review

Leso

Vetrani

Sicignano

et al. 2020

IJERPH

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Thyroid hormones are regulated by the pituitary thyroid stimulating hormone (TSH), whose secretion presents a circadian rhythmicity. Indeed, it is conceivable that shift- and night shift-work, affecting sleep-wake rhythms, may impact thyroid functionality. Therefore, the aim of the present review was to provide an overview on the association between shift- and night shift-work and thyroid hormonal changes and disease development. A systematic review of studies available in PubMed, Scopus, and ISI Web of Science databases was performed. A positive association between night shift-work and increased TSH concentrations was reported by most of the reviewed investigations. Inconclusive evidence was available on thyroid diseases. However, the limited number of studies, the noticeable heterogeneity in the shift-work scheduling, in terms of amount, duration, type of shift- or night shift-work, prevents easily integrating findings and extrapolating definite conclusions. Further investigation seems necessary to better define the relationship between shift schedules and different thyroid outcomes, and possible long-term implications of early functional changes. Overall, this may support the adoption of advanced risk assessment and management strategies aimed to achieve a safer workplace organization and a timely, responsible realization of all the benefits of a 24-h economy.

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Section: Night On-call-work and Thyroid Hormonal Changessupporting

confidence: 53%

Section: Resultsmentioning

confidence: 99%

Section: Night On-call-work and Thyroid Hormonal Changesmentioning

confidence: 99%

See 1 more Smart Citation

The Impact of Shift-Work and Night Shift-Work on Thyroid: A Systematic Review

Leso

Vetrani

Sicignano

et al. 2020

IJERPH

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“…In our study, users were considered to have normal sleep values if their weekly sleep average was less than 0•5 SD below their overall sleep average, as nights of short sleep duration have been shown to result in elevated heart rate the following day. 19,20 We found that our correlations improved slightly when we classified people as displaying normal values when they had low sleep. In the future, improved measurements of stress by wearable devices, either by detection of voice changes or galvanic skin response, could further improve our ability to identify other non-infectious causes of elevated RHR.…”

Section: Discussionmentioning

confidence: 80%

Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study

Radin

Wineinger

Topol

et al. 2020

The Lancet Digital Health

270

211

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Background Acute infections can cause an individual to have an elevated resting heart rate (RHR) and change their routine daily activities due to the physiological response to the inflammatory insult. Consequently, we aimed to evaluate if population trends of seasonal respiratory infections, such as influenza, could be identified through wearable sensors that collect RHR and sleep data. Methods We obtained de-identified sensor data from 200 000 individuals who used a Fitbit wearable device from March 1, 2016, to March 1, 2018, in the USA. We included users who wore a Fitbit for at least 60 days and used the same wearable throughout the entire period, and focused on the top five states with the most Fitbit users in the dataset: California, Texas, New York, Illinois, and Pennsylvania. Inclusion criteria included having a self-reported birth year between 1930 and 2004, height greater than 1 m, and weight greater than 20 kg. We excluded daily measurements with missing RHR, missing wear time, and wear time less than 1000 min per day. We compared sensor data with weekly estimates of influenza-like illness (ILI) rates at the state level, as reported by the US Centers for Disease Control and Prevention (CDC), by identifying weeks in which Fitbit users displayed elevated RHRs and increased sleep levels. For each state, we modelled ILI case counts with a negative binomial model that included 3-week lagged CDC ILI rate data (null model) and the proportion of weekly Fitbit users with elevated RHR and increased sleep duration above a specified threshold (full model). We also evaluated weekly change in ILI rate by linear regression using change in proportion of elevated Fitbit data. Pearson correlation was used to compare predicted versus CDC reported ILI rates. Findings We identified 47 249 users in the top five states who wore a Fitbit consistently during the study period, including more than 13•3 million total RHR and sleep measures. We found the Fitbit data significantly improved ILI predictions in all five states, with an average increase in Pearson correlation of 0•12 (SD 0•07) over baseline models, corresponding to an improvement of 6•3-32•9%. Correlations of the final models with the CDC ILI rates ranged from 0•84 to 0•97. Week-to-week changes in the proportion of Fitbit users with abnormal data were associated with week-to-week changes in ILI rates in most cases. Interpretation Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks.

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“…Researchers believe that the hormonal changes may depend on many interfering factors including insufficient sleep [47], emotional pressure and caloric demands ] 48 , 49 [ , and therefore these factors all may disrupt the correct thyroid function [50]. As a result, controlling these nuisance factors increases the validity of findings.…”

Section: Discussionmentioning

confidence: 99%

Shorter recovery time following high-intensity interval training induced higher body fat loss among overweight women

et al. 2018

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Background: High intensity interval training (HIIT) has been widely employed as an exercise protocol to reduce fat, and also in addition, interval recovery periods are the most important factors which can have great impact on weight loss. Therefore, the aim of this study was the evaluation of different recovery time between HIIT program on metabolic responses and weight loss in overweight women. Methods: Twenty-four overweight (BMI 29.5±3.5 kg/m2) volunteer women were randomly assigned into three groups (n=8/group) to study the effects of different recovery times: (group 1; HIIT with 60/60 activity-rest ratio (sec), group 2; HIIT with 60/30 activity-rest ratio (sec), and group 3 was set as a control. The participants performed 3 times per week 4 bouts/session (80% of Heart Rate Reserve). The exercise program gradually increased to 10 bouts/session. Results: The most important findings of this study were a change in the Body fat percentage (BF %) in the between group comparison: group1 (40.5±0.9), group 2 (41.2±0.7) and group 3 (41.1±1.1). Compared to the control group the 60/30 sec HIIT resulted in a significant decrease in BF % (p=0.002). However, no other significant differences in the body composition were found. Either there were no significant differences between the groups in T4, T3 and TSH, cortisol, HGH, FBS, blood insulin, insulin resistance insulin sensitivity or fatnessassociated hormones. Conclusions: In conclusion, considerable decrease in BF % in the 60/30 sec. rest interval group indicates that 30 sec recovery period in HIIT may reduce fat % more efficiently than 60 sec.

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Effects of a 24‐hr‐shift‐related short‐term sleep deprivation on cardiac function: A cardiac magnetic resonance‐based study

Cited by 25 publications

References 34 publications

The Impact of Shift-Work and Night Shift-Work on Thyroid: A Systematic Review

The Impact of Shift-Work and Night Shift-Work on Thyroid: A Systematic Review

Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study

Shorter recovery time following high-intensity interval training induced higher body fat loss among overweight women

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